Scholar Info

Sarath Janga

Department of Biohealth Informatics, School of Informatics and Computing, Indianapolis, IUPUI
ude[dot]iupui[at]agnajcs

Rapid detection of viral based infectious diseases

The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in Wuhan (Hubei, China) in December 2019 has been declared a pandemic by the World Health Organization (WHO) due to its easy human to human transmission, making it a global public health concern. Coronaviruses are enveloped single-stranded ribonucleic acid (RNA) viruses with characteristic “crown” like appearance under two-dimensional transmission electron microscopy. Infections caused by these viruses result in severe pneumonia, fever and breathing difficulty. Currently there is a lack of effective vaccines and antiviral medication that has led to a global outbreak of SARS-CoV-2. Due to rapidly evolving nature of coronaviruses, their identification has become increasingly challenging. Therefore, it is important to develop diagnostic methods that can detect the virus rapidly, to prevent its transmission. Currently, most clinical diagnostic tests for viruses depend on detecting a viral antigen or rely on PCR amplification of viral nucleic acid derived from biological samples. These two approaches offer trade-offs in benefits: antigen tests (including current Point-Of-Care Tests [POCT]) are typically rapid but have low sensitivity, while PCR is more time-consuming but also more sensitive. Irrespective of the test used, most clinical diagnostic facilities report a non-quantitative (binary) diagnostic result, and the data generated have limited capacity to inform insights into epidemiological linkage, vaccine efficacy, or antiviral susceptibility. Hence, there is an urgent need to generate new diagnostic tests that combine POCT, speed, sensitivity, detection of coinfection by other viral strains, and generation of quantitative or semi-quantitative data that can be used to identify drug resistance. Such data may also be used to reconstruct phylogeny to inform surveillance, public health strategy, and vaccine design. My lab has been working to employ “third-generation” portable, real-time bench top sequencers which use nanopores, to develop novel experimental protocols and computational algorithms to not only detect the presence of pathogens but also map their variability across clinical samples, to facilitate public health surveillance. More recently, my lab has been combining an efficient, novel and high-throughput viral RNA isolation methods accompanied with nanopore sequencing to develop automated computational software for real time detection of COVID19. This has be applied to detection of Coronavirus 2019 (SARS-CoV-2, the COVID19 virus) strains in clinical samples using an approved IRB at IU clinical pathology lab, for developing a novel rapid, real-time and scalable test which is available in the clinics to help the healthcare workers who are at the front lines of care and are getting exposed to infections. An additional outcome of the proposed work is to develop a comprehensive serotyping map of the COVID19 strains prevalent in Indiana by performing single molecule direct RNA sequencing of the clinical isolates.